2014
DOI: 10.1088/1748-9326/9/12/124009
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Modeling very large-fire occurrences over the continental United States from weather and climate forcing

Abstract: Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ∼60 km spatial and weekly temporal resolutions using solely atmospheric predictors. Climate−fire relationships on interannual timescales were evident, with wetter conditions than normal in the previous growing season en… Show more

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Cited by 103 publications
(115 citation statements)
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“…Studies have shown that large fires are driven by antecedent climatic factors that promote fuel abundance plus extreme fire weather and climatic factors (e.g., wind, drought, high temperatures) at the time of fire ignition [3,18,26,34,49,56]. However, our results suggest that the pattern between fire size and biomass varied substantially within and across U.S. ecoregions.…”
Section: Environmental Controls On Large Fire Sizecontrasting
confidence: 61%
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“…Studies have shown that large fires are driven by antecedent climatic factors that promote fuel abundance plus extreme fire weather and climatic factors (e.g., wind, drought, high temperatures) at the time of fire ignition [3,18,26,34,49,56]. However, our results suggest that the pattern between fire size and biomass varied substantially within and across U.S. ecoregions.…”
Section: Environmental Controls On Large Fire Sizecontrasting
confidence: 61%
“…Large wildfire events can be economically costly and often have pronounced negative consequences for ecosystems and societies, including losses of structures and even lives [18,49]. In recent decades, the size and number of large wildfires has increased [2,3,5], and extreme fires (termed "mega-fires") are becoming more common [11,50,51].…”
Section: Discussionmentioning
confidence: 99%
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“…Other authors have approached the problem of producing forest fire risk maps using methods such as GIS (Vázquez and Moreno, 1998), logistic regression (Preisler and Westerling, 2007), autologistic regression (Koutsias, 2003) and empirical generalized linear models (Barbero et al, 2014) among others. Most of such approaches are either based on pure descriptive methods or ignore the presence of spatial dependence observed in the data.…”
Section: Discussionmentioning
confidence: 99%